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Artificial intelligence is increasingly embedded in everyday communication, not only as a tool for generating or modifying messages, but as a condition that reshapes how meanings become available, circulated, and stabilized. Existing research has often focused on trust, anthropomorphism, or user attitudes toward AI. Less attention has been given to how AI-mediated environments may alter the process through which meanings become collectively shared. This article addresses that gap by using Symbolic Convergence Theory to examine how AI-mediated environments reshape the process through which meanings become shared, stabilized, and cognitively available. It treats fantasy themes, fantasy types, symbolic convergence, and rhetorical vision as linked levels in the formation of shared symbolic reality. Building on this framework, the article argues that AI-mediated environments reconfigure symbolic convergence in three ways: by accelerating the production of symbolic materials, expanding their circulation, and reinforcing their stabilization through repetition and prioritization. These changes matter not only at the level of communication, but also at the level of cognition. When meanings are increasingly encountered in prestructured, repeated, and personalized forms, interpretation may become narrower, more dependent on familiar cues, and more shaped by shifting cognitive authority. Rather than treating AI simply as an artificial social actor, the article proposes that AI should also be understood as part of a transformed symbolic environment within which human cognition operates. This perspective offers a conceptually grounded account of how AI reshapes shared meaning formation and, in doing so, alters the conditions under which human interpretation and judgment take shape.
Chen et al. (Tue,) studied this question.